%%% general part

@InProceedings{emulab,
  author = {Brian White and Jay Lepreau and Leigh Stoller and Robert Ricci and Shashi Guruprasad and Mac Newbold and Mike Hibler and Chad Barb and Abhijeet Joglekar},
  title={{An Integrated Experimental Environment for Distributed Systems and Networks}},
  booktitle = {{Proc.\ of the Fifth Symposium on Operating Systems Design and Implementation}},
  organization = {{USENIX} {Association}},
  address = {Boston, MA},
  month  = dec,
  year   = 2002,
  pages  = "255--270"
}


@article{deterlab,
  title={{Cyber Defense Technology Networking and Evaluation}},
  author={Bajcsy, R. and Benzel, T. and Bishop, M. and Braden, B. and Brodley, C. and Fahmy, S. and Floyd, S. and Hardaker, W. and Joseph, A. and Kesidis, G. and others},
  journal={Communications of the ACM},
  volume={47},
  number={3},
  pages={58--61},
  year={2004},
  publisher={ACM}
}


@inproceedings{deter,
  title={{Experience with DETER: A Testbed for Security Research}},
  author={Benzel, T. and Braden, R. and Kim, D. and Neuman, C. and Joseph, A. and Sklower, K. and Ostrenga, R. and Schwab, S.},
  booktitle={Testbeds and Research Infrastructures for the Development of Networks and Communities, 2006. TRIDENTCOM 2006. 2nd International Conference on},
  pages={10--pp},
  year={2006},
  organization={IEEE}
}


@article{planetlab,
  title={{Planetlab: an Overlay Testbed for Broad-coverage Services}},
  author={Chun, B. and Culler, D. and Roscoe, T. and Bavier, A. and Peterson, L. and Wawrzoniak, M. and Bowman, M.},
  journal={ACM SIGCOMM Computer Communication Review},
  volume={33},
  number={3},
  pages={3--12},
  year={2003},
  publisher={ACM}
}

@inproceedings{sonia1,
  title={{Emulation versus Simulation: A Case Study of TCP-targeted Denial of Service Attacks}},
  author={Chertov, R. and Fahmy, S. and Shroff, N.B.},
  booktitle={Testbeds and Research Infrastructures for the Development of Networks and Communities, 2006. TRIDENTCOM 2006. 2nd International Conference on},
  pages={10--pp},
  year={2006},
  organization={IEEE}
}


@article{sonia2,
  title={{Fidelity of Network Simulation and Emulation: A Case Study of TCP-targeted Denial of Service Attacks}},
  author={Chertov, R. and Fahmy, S. and Shroff, N.B.},
  journal={ACM Transactions on Modeling and Computer Simulation (TOMACS)},
  volume={19},
  number={1},
  pages={1--29},
  year={2008},
  publisher={ACM}
}


@inproceedings{starbed,
  title={{StarBED and SpringOS: large-scale General Purpose Network Testbed and Supporting Software}},
  author={Miyachi, T. and Chinen, K. and Shinoda, Y.},
  booktitle={Proceedings of the 1st international conference on Performance evaluation methodolgies and tools},
  pages={30--es},
  year={2006},
  organization={ACM}
}

@inproceedings{orbit,
  title={{Overview of the ORBIT Radio Grid Testbed for Evaluation of Next-generation Wireless Network Protocols}},
  author={Raychaudhuri, D. and Seskar, I. and Ott, M. and Ganu, S. and Ramachandran, K. and Kremo, H. and Siracusa, R. and Liu, H. and Singh, M.},
  booktitle={Wireless Communications and Networking Conference, 2005 IEEE},
  volume={3},
  pages={1664--1669},
  year={2005},
  organization={IEEE}
}

@inproceedings{geni,
  title={{The GENI Meta-Operations Center}},
  author={Herron, J.P. and Fowler, L. and Small, C.},
  booktitle={Proceedings of the 2008 Fourth IEEE International Conference on eScience},
  pages={384--385},
  year={2008},
  organization={IEEE Computer Society}
}

@book{kruskal,
  title={Engineering statistics},
  author={Hogg, R.V. and Ledolter, J.},
  year={1987},
  publisher={New York: MacMillan}
}



%%% related work

@inproceedings{OnlineMeasurement,
language = {English},
copyright = {Copyright 2006, The Institution of Engineering and Technology},
title = {A {T}estbed for {A}gent-based {M}ulti-purpose {E}xtensible {A}ctive {M}easurement},
journal = {2006 2nd International Conference on Testbeds and Research Infrastructures for the Development of Networks and Communities (IEEE Cat. No. 06EX1274C)},
author = {Zhanikeev, M. and Tanaka, Y.},
year = {2006},
pages = {9 pp. - },
address = {Piscataway, NJ, USA},
abstract = {Requirements for a measurement platform nowadays have advanced to the level at which a number of different in principle measurement techniques have to be performed simultaneously. Quite common are hybrids of passive data collections and event-driven active measurements. This calls for a highly extensible measurement platform, in which design of the probe and parameters of probing could be accessible in realtime while the measurement itself is being performed. In this paper, we introduce a testbed application that was developed with the initial requirement to be fit for a number of different applications, such as bandwidth measurement, performance prediction, tomography, and others, without a loss of performance characteristics},
}


@inproceedings{simpleTestBed,
language = {English},
copyright = {Copyright 2005, IEE},
title = {Automatic {C}onfiguration and {E}xecution of {I}nternet {E}xperiments on an {A}ctual {N}ode-based {T}estbed},
journal = {Proceedings. First International Conference on Testbeds and Research Infrastructures for the Development of Networks and Communities},
author = {Miyachi, T. and Chinen, K. and Shinoda, Y.},
year = {2005},
pages = {274 - 82},
address = {Los Alamitos, CA, USA},
abstract = {Software simulators are widely used for validation and evaluation of new network technologies and services. Using software simulators is a good way to validate algorithms or observing microbehavior of communication protocols. There are, however, problems with software simulators. Most software simulators require target systems to be described under their own modelling scheme, often using their own modelling language. These descriptions are usually different from what will actually be running as products. It is clear that these products should be validated someway. Time required to run software simulation become problematic also, as we try to simulate realistic target system under realistic environment where nontrivial aggregation of complex network services come into play. We adopt an approach to prepare a configurable testbed using actual nodes. Experiment topologies are created on this testbed virtually without changing physical connections, because the cost of building such experiment environments is very large. Since users of such testbed have to perform many steps to execute the desired experiments on such environment, we design the system that supports the users to execute their experiments. Using our system, all the user have to perform is preparing a experiment configuration file. Our system will execute experiments according to the configuration file. This paper shows the design of our supporting system models, steps of experiment with our system and an example of user's scenario},
}


@inproceedings{OpenRoads,
language = {English},
copyright = {Compilation and indexing terms, Copyright 2011 Elsevier Inc.},
copyright = {Compendex},
title = {The {S}tanford {O}pen{R}oads {D}eployment},
journal = {WiNTECH'09 - Proc. 4th ACM International Workshop on Wireless Network Testbeds, Experimental Evaluation and Characterization},
author = {Yap, Kok-Kiong and Kobayashi, Masayoshi and Underhill, David and Seetharaman, Srinivasan and Kazemian, Peyman and McKeown, Nick},
year = {2009},
pages = {59 - 66},
address = {Beijing, China},
abstract = {We have built and deployed OpenRoads [11], a testbed that allows multiple network experiments to be conducted concurrently in a production network. For example, multiple routing protocols, mobility managers and network access controllers can run simultaneously in the same network. In this paper, we describe and discuss our deployment of the testbed at Stanford University. We focus on the challenges we faced deploying in a production network, and the tools we built to overcome these challenges. Our goal is to gain enough experience for other groups to deploy OpenRoads in their campus network. Copyright 2009 ACM.},
}


@inproceedings{StarBED2,
language = {English},
copyright = {Copyright 2008, The Institution of Engineering and Technology},
title = {StarBED2: {L}arge-scale, {R}ealistic and {R}eal-time {T}estbed for {U}biquitous {N}etworks},
journal = {2007 3rd International Conference on Testbeds and Research Infrastructues for the Development of Networks and Communities - TridentCom '07},
author = {Nakata, J. and Uda, S. and Miyaclii, T. and Masui, K. and Beuran, R. and Yasuo Tan and Chinen, K.-i. and Shinoda, Y.},
year = {2007},
pages = {124 - 30},
address = {Piscataway, NJ, USA},
abstract = {Nowadays many new technologies are being developed and introduced for Internet, home networks, and sensor networks. The new technologies must be evaluated in detail before deployment. However the above mentioned networks have a large number of nodes and a complicated topology. Therefore it is difficult to analyze such networks using typical network simulators. Accordingly testbeds for these networks must be able to perform accurately emulation of large-scale networks with a complex topology. In order to implement a testbed that satisfies these requirements, we developed a large-scale, realistic and real-time network testbed, StarBED, using hundreds of PCs, and switched networks. We are now implementing StarBED2, which expands StarBED so as to be suitable for emulating ubiquitous networks by introducing several new concepts. In this paper we describe first the present StarBED, its design concept, overall architecture, implemented functionalities, and some of the experiments we performed. Then we introduce StarBED2, its design policy, architecture, and additional components.},
}


@inproceedings{TORI,
language = {English},
copyright = {Compilation and indexing terms, Copyright 2011 Elsevier Inc.},
copyright = {Compendex},
title = {{TORI}: {U}ser {P}rovided {F}uture {N}etworking {T}estbeds},
journal = {Proceedings - 2009 IEEE International Conference on Communications Workshops, ICC 2009},
author = {Stiemerling, M. and Brunner, M. and Kiesel, S. and Fu, X.},
year = {2009},
address = {Dresden, Germany},
abstract = {The usage of testbeds is considered a key tool for exploring the development of new protocols and network architectures in the area of network research. Testbeds, together with simulations, are the basic tool set of network researchers to drive research, but often it is impossible to get feedback from real deployments and their respective data traffic. Today's major testbed facilities, e.g., VINI and PlanetLab, aim at emulating the behavior of large-scale networks, but they are still several orders of magnitude smaller than the deployed operational network infrastructure. We argue that it is time to extend network research beyond theoretical and testbed approaches towards a dynamic, peer-to-peer based testbed environment, similar to the approach taken by seti@home and BOINC. We aim at expanding the total number of participating nodes in an experiment and at experimenting on existing operational infrastructure with its entirely uncontrollable environment. Our vision presented in this paper, the Testbed on Real Infrastructure (TORI), includes regular end hosts (peers) in an experiment by deploying and executing the experimental software on these peers and to form an overlay network upon them. The main difference of our TORI approach compared to others is installing new technologies and testing them with the operational infrastructure. &copy; 2009 IEEE.},
}


@inproceedings{GlobusPlanetLab,
language = {English},
copyright = {Compilation and indexing terms, Copyright 2011 Elsevier Inc.},
title = {Globus and {P}lanetLab {R}esource {M}anagement {S}olutions {C}ompared},
journal = {IEEE International Symposium on High Performance Distributed Computing, Proceedings},
author = {Ripeanu, Matei and Bowman, Mic and Chase, Jeffrey S. and Foster, Ian and Milenkovic, Milan},
year = {2004},
pages = {246 - 255},
issn = {10828907},
address = {Honolulu, HI, United states},
abstract = {PlanetLab and Globus Toolkit are gaining widespread adoption in their respective communities. Although designed to solve different problems-PlanetLab is deploying a worldwide infrastructure testbed for experimenting with network services, while Globus is offering general, standards-based, software for running distributed applications over aggregated, shared resources - both build infrastructures that enable federated, extensible, and secure resource sharing across trust domains. Thus, it is instructive to compare their resource management solutions. To this end, we review the approaches taken in the two systems, attempt to trace back to starting assumptions the differences in these approaches, and explore scenarios where the two platforms can cooperate to the benefit of both user communities. We believe that this is a key first step to identifying pieces that could be shared by the two communities, pieces that are complementary, and how Globus and PlanetLab might ultimately evolve together.},
}


@inproceedings{floorControl,
language = {English},
copyright = {Compilation and indexing terms, Copyright 2011 Elsevier Inc.},
copyright = {Compendex},
title = {Implementation and {E}mpirical {E}valuations of {F}loor {C}ontrol {P}rotocols on {P}lanetlab {N}etwork},
journal = {Proceedings of the 47th Annual Southeast Regional Conference, ACM-SE 47},
author = {Banik, Shankar M. and Daigle, Logan P. and Chang, Tao-Hsiang},
year = {2009},
address = {Clemson, SC, United states},
abstract = {Nowadays users from different parts of the world participate in collaborative applications (online games, video-conferencing, distributed large-scale simulations) over the Internet. These applications require that at any point in time only one user can exclusively access a shared resource. The problem of providing exclusive access to shared resources in collaborative applications is known as the floor control problem. Centralized and distributed protocols for floor control problem have been proposed in the literature and simulation experiments have been conducted to study the performance of these protocols. None of these protocols have been tested on the real Internet. In this paper, we present empirical evaluations of different floor control protocols on PlanetLab network which is an overlay testbed that connects several academic institutions and industrial research labs all over the world in a virtual network. We have implemented two flavors of distributed solutions - the randomized Aloha and the scheduled DQDB (Distributed Queue Dual Bus) based protocols. We have also implemented the centralized protocol where the users send floor requests to a central node and the central node schedules the floor requests based on First in First Out. The protocols are implemented using Berkeley Software Distribution (BSD) sockets API. For the experiments, nodes from different PlanetLab sites are selected to resemble that users from different parts of the world are participating in a collaborative application. Average waiting time to gain a floor is used as the performance metric. &copy;2009 ACM.},
}


@article{CoMon,
language = {English},
copyright = {Compilation and indexing terms, Copyright 2011 Elsevier Inc.},
copyright = {Compendex},
title = {Co{M}on: {A} {M}ostly-scalable {M}onitoring {S}ystem for {P}lanet{L}ab},
journal = {Operating Systems Review (ACM)},
author = {Park, KyoungSoo and Pai, Vivek S.},
volume = {40},
number = {1},
year = {2006},
pages = {65 - 74},
issn = {01635980},
abstract = {CoMon is an evolving, mostly-scalable monitoring system for PlanetLab that has the goal of presenting environment-tailored information for both the administrators and users of the PlanetLab global testbed. In addition to passively reporting metrics provided by the operating system, CoMon also actively gathers a number of metrics useful for developers of networked systems. Using CoMon, PlanetLab administrators and users can easily spot problematic machines, where the problem may arise from the machine itself, local configuration/environment problems, or the workload running on the machine. Furthermore, users can easily observe many properties of all of the experiments running across multiple PlanetLab nodes, facilitating not only their own experiment monitoring and debugging, but also helping scale the task of finding PlanetLab problems. In this paper we describe CoMon's design and operation, including what kinds of data are gathered, the scale of the processing involved, and the approaches we have taken to keep CoMon running. Our goal is not only to illustrate the kinds of problems faced in this environment, but also to invite others to participate, either by experimenting with the data generated by CoMon, or by building on the CoMon system itself.},
}


@inproceedings{Vendetta,
language = {English},
copyright = {Copyright 2008, The Institution of Engineering and Technology},
title = {Vendetta: {A} {T}ool for {F}lexible {M}onitoring and {M}anagement of {D}istributed {T}estbeds},
journal = {2007 3rd International Conference on Testbeds and Research Infrastructues for the Development of Networks and Communities - TridentCom '07},
author = {Rensfelt, O. and Larzon, L.-A. and Westergren, S.},
year = {2007},
pages = {Z13-Z20 - },
address = {Piscataway, NJ, USA},
abstract = {Writing a powerful tool for monitoring and management of a testbed can have a positive effect when doing research on the testbed. Despite this, many testbeds use primitive scripts for data collection, code updates and other basic tasks. We introduce Vendetta, a flexible and powerful platform for monitoring and management of distributed testbeds. It is designed to be relatively easy to adapt to different testbeds by having a modular design, being written in Java and defining much of the testbed-specific behavior in two configuration files. The novelty in comparison with similar tools is the integration of a GUI supporting 30 graphics, flexible monitoring and management into one single tool. We will present the general design of Vendetta and then illustrate how it has been used for monitoring and management of an experimental DHT deployment running on PlanetLab. Experiences from this combination shows that usage of a tool like Vendetta simplifies testbed management and makes it easier to discover and analyze different phenomena.},
}


@article{meshnet,
language = {English},
copyright = {Compilation and indexing terms, Copyright 2011 Elsevier Inc.},
copyright = {Compendex},
title = {Experiences {F}rom the {D}esign, {D}eployment, and {U}sage of the {UCSB} {M}eshnet {T}estbed},
journal = {IEEE Wireless Communications},
author = {Lundgren, Henrik and Ramachandran, Krishna and Belding-Royer, Elizabeth and Almeroth, Kevin and Benny, Michael and Hewatt, Andrew and Touma, Alexander and Jardosh, Amit},
volume = {13},
number = {2},
year = {2006},
pages = {18 - 29},
issn = {15361284},
abstract = {In this article we report on our effort and experience in designing, deploying, and using our 30-node wireless mesh testbed, the University of California at Santa Barbara (UCSB) MeshNet. Compared to simulation, the construction and utilization of a wireless mesh testbed poses many new challenges. We discuss the challenges with distributed testbed management, nonintrusive and distributed monitoring, and node status visualization. These are vital components in a sustainable wireless mesh testbed, but at the same time nontrivial to design and realize. As a case study, we present the UCSB MeshNet architecture, including its management, monitoring, and visualization systems. We share our lessons learned from this effort and believe that they will be valuable to other researchers who develop experimental wireless mesh networks. &copy; 2006 IEEE.},
}




%%% topology related

@inproceedings{LEAP,
language = {English},
copyright = {Compilation and indexing terms, Copyright 2011 Elsevier Inc.},
copyright = {Compendex},
title = {Mining {S}ignificant {G}raph {P}atterns by {L}eap {S}earch},
journal = {Proceedings of the ACM SIGMOD International Conference on Management of Data},
author = {Yan, Xifeng and Cheng, Hong and Han, Jiawei and Yu, Philip S.},
year = {2008},
pages = {433 - 444},
issn = {07308078},
address = {Vancouver, BC, Canada},
abstract = {With ever-increasing amounts of graph data from disparate sources, there has been a strong need for exploiting significant graph patterns with user-specified objective functions. Most objective functions are not antimonotonic, which could fail all of frequency-centric graph mining algorithms. In this paper, we give the first comprehensive study on general mining method aiming to find most significant patterns directly. Our new mining framework, called LEAP (Descending Leap Mine), is developed to exploit the correlation between structural similarity and significance similarity in a way that the most significant pattern could be identified quickly by searching dissimilar graph patterns. Two novel concepts, structural leap search and frequency descending mining, are proposed to support leap search in graph pattern space. Our new mining method revealed that the widely adopted branch-and-bound search in data mining literature is indeed not the best, thus sketching a new picture on scalable graph pattern discovery. Empirical results show that LEAP achieves orders of magnitude speedup in comparison with the state-of-the-art method. Furthermore, graph classifiers built on mined patterns outperform the up-to-date graph kernel method in terms of efficiency and accuracy, demonstrating the high promise of such patterns. Copyright 2008 ACM.},
}


@inproceedings{kNN,
language = {English},
copyright = {Compilation and indexing terms, Copyright 2011 Elsevier Inc.},
copyright = {Compendex},
title = {GraphSig: a {S}calable {A}pproach to {M}ining {S}ignificant {S}ubgraphs in {L}arge {G}raph {D}atabases},
journal = {Proceedings - International Conference on Data Engineering},
author = {Ranu, Sayan and Singh, Ambuj K.},
year = {2009},
pages = {844 - 855},
issn = {10844627},
address = {Shanghai, China},
abstract = {Graphs are being increasingly used to model a wide range of scientific data. Such widespread usage of graphs has generated considerable interest in mining patterns from graph databases. While an array of techniques exists to mine frequent patterns, we still lack a scalable approach to mine statistically significant patterns, specifically patterns with low p-values, that occur at low frequencies. We propose a highly scalable technique, called GraphSig, to mine significant subgraphs from large graph databases. We convert each graph into a set of feature vectors where each vector represents a region within the graph. Domain knowledge is used to select a meaningful feature set. Prior probabilities of features are computed empirically to evaluate statistical significance of patterns in the feature space. Following analysis in the feature space, only a small portion of the exponential search space is accessed for further analysis. This enables the use of existing frequent subgraph mining techniques to mine significant patterns in a scalable manner even when they are infrequent. Extensive experiments are carried out on the proposed techniques, and empirical results demonstrate that GraphSig is effective and efficient for mining significant patterns. To further demonstrate the power of significant patterns, we develop a classifier using patterns mined by GraphSig. Experimental results show that the proposed classifier achieves superior performance, both in terms of quality and computation cost, over state-of-the-art classifiers. &copy; 2009 IEEE.},
}


@inproceedings{SFS,
language = {English},
copyright = {Compilation and indexing terms, Copyright 2011 Elsevier Inc.},
copyright = {Compendex},
title = {Structure {F}eature {S}election for {G}raph {C}lassification},
journal = {International Conference on Information and Knowledge Management, Proceedings},
author = {Fei, Hongliang and Huan, Jun},
year = {2008},
pages = {991 - 999},
address = {Napa Valley, CA, United states},
abstract = {With the development of highly efficient graph data collection technology in many application fields, classification of graph data emerges as an important topic in the data mining and machine learning community. Towards building highly accurate classification models for graph data, here we present an efficient graph feature selection method. In our method, we use frequent subgraphs as features for graph classification. Different from existing methods, we consider the spatial distribution of the subgraph features in the graph data and select those ones that have consistent spatial location. We have applied our feature selection methods to several cheminformatics benchmarks. Our method demonstrates a significant improvement of prediction as compared to the state-of-the-art methods. Copyright 2008 ACM.},
}


@inproceedings{Boost,
language = {English},
copyright = {Copyright 1997, IEE},
title = {Experiments with a {N}ew {B}oosting {A}lgorithm},
journal = {Machine Learning. Proceedings of the Thirteenth International Conference (ICML '96)},
author = {Freund, Y. and Schapire, R.E.},
year = {1996},
pages = {148 - 56},
address = {San Francisco, CA, USA},
abstract = {In an earlier paper, we introduced a new &ldquo;boosting&rdquo; algorithm called AdaBoost which, theoretically, can be used to significantly reduce the error of any learning algorithm that consistently generates classifiers whose performance is a little better than random guessing. We also introduced the related notion of a &ldquo;pseudo-loss&rdquo; which is a method for forcing a learning algorithm of multi-label concepts to concentrate on the labels that are hardest to discriminate. In this paper, we describe experiments we carried out to assess how well AdaBoost with and without pseudo-loss, performs on real learning problems. We performed two sets of experiments. The first set compared boosting to Breiman's &ldquo;bagging&rdquo; method when used to aggregate various classifiers (including decision trees and single attribute-value tests). We compared the performance of the two methods on a collection of machine-learning benchmarks. In the second set of experiments, we studied in more detail the performance of boosting using a nearest-neighbor classifier on an OCR problem},
}


@article{Ullman,
language = {English},
copyright = {Copyright 1976, IEE},
title = {An {A}lgorithm for {S}ubgraph {I}somorphism},
journal = {Journal of the Association for Computing Machinery},
author = {Ullmann, J.R.},
volume = { 23},
number = { 1},
year = {1976/01/},
pages = {31 - 42},
issn = {0004-5411},
address = {USA},
abstract = {Subgraph isomorphism can be determined by means of a brute-force tree-search enumeration procedure. In this paper a new algorithm is introduced that attains efficiency by inferentially eliminating successor nodes in the tree search. To assess the time actually taken by the new algorithm, subgraph isomorphism, clique detection, graph isomorphism, and directed graph isomorphism experiments have been carried out with random and with various nonrandom graphs. A parallel asynchronous logic-in-memory implementation of a vital part of the algorithm is also described, although this hardware has not actually been built. The hardware implementation would allow very rapid determination of isomorphism},
}


@article{VF2,
language = {English},
copyright = {Compilation and indexing terms, Copyright 2011 Elsevier Inc.},
copyright = {Compendex},
title = {A (sub)graph {I}somorphism {A}lgorithm for {M}atching {L}arge {G}raphs},
journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
author = {Cordella, Luigi P. and Foggia, Pasquale and Sansone, Carlo and Vento, Mario},
volume = {26},
number = {10},
year = {2004},
pages = {1367 - 1372},
issn = {01628828},
abstract = {We present an algorithm for graph isomorphism and subgraph isomorphism suited for dealing with large graphs. A first version of the algorithm has been presented in a previous paper, where we examined its performance for the isomorphism of small and medium size graphs. The algorithm is improved here to reduce its spatial complexity and to achieve a better performance on large graphs; its features are analyzed in detail with special reference to time and memory requirements. The results of a testing performed on a publicly available database of synthetically generated graphs and on graphs relative to a real application dealing with technical drawings are presented, confirming the effectiveness of the approach, especially when working with large graphs. &copy; 2004 IEEE.},
}


@inproceedings{BLISS,
language = {English},
copyright = {Compilation and indexing terms, Copyright 2011 Elsevier Inc.},
copyright = {Compendex},
title = {Engineering an {E}fficient {C}anonical {L}abeling {T}ool for {L}arge and {S}parse {G}raphs},
journal = {Proceedings of the 9th Workshop on Algorithm Engineering and Experiments and the 4th Workshop on Analytic Algorithms and Combinatorics},
author = {Junttila, Tommi and Kaski, Petteri},
year = {2007},
pages = {135 - 149},
address = {New Orleans, LA, United states},
abstract = {The problem of canonically labeling a graph is studied. Within the general framework of backtracking algorithms based on individualization and refinement, data structures, subroutines, and pruning heuristics especially for fast handling of large and sparse graphs are developed. Experiments indicate that the algorithm implementation in most cases clearly outperforms existing state-of-the-art tools.},
}

@book{nauty,
  title={{Practical {G}raph {I}somorphism}},
  author={McKay, B.D. and Vanderbilt University. Dept. of Computer Science},
  year={1981},
  publisher={Citeseer}
}

@book{Valiente,
  title={{Algorithms on {T}rees and {G}raphs}},
  author={Valiente, G.},
  isbn={3540435506},
  year={2002},
  publisher={Springer Verlag}
}

@article{conauto,
  title={{Graph Isomorphism Testing Without Full Automorphism Group Computation}},
  author={L{\'o}pez-Presa, J.L. and Fern{\'a}ndez, A.},
  year={2004},
  publisher={Citeseer}
}

@MISC{igraph,
	title = {igraph},
	howpublished = "{http://igraph.sourceforge.net/}",
}

@MISC{BGL,
	title = {{Boost Graph Library}},
	howpublished = "{http://www.boost.org/}",
}

@MISC{JgraphT,
	title = {{JgraphT}},
	howpublished = "{http://www.jgrapht.org/}",
}

@MISC{yWorks,
	title = {{yWorks}},
	howpublished = "{http://www.yworks.com/}",
}

@MISC{LEDA,
	title = {{LEDA}},
	howpublished = "{http://www.algorithmic-solutions.com/}",
}

@MISC{topologies,
    title = {{Network Topologies}},
    howpublished = {http://en.wikipedia.org/wiki/Network\_topology},
}

@MISC{graphiso,
    title = {{Graph Isomorphism Problem}},
    howpublished = {http://en.wikipedia.org/wiki/Graph\_isomorphism\_problem},
}

@MISC{PlanetLabUsage,
    title = {{PlanetLab Usage Statistics}},
    howpublished = {http://everlab.cs.huji.ac.il/plcstats},
}

@MISC{schooner,
    title = {{Schooner WAIL (Wisconsin Advanced Internet Laboratory)}},
    howpublished = {http://www.schooner.wail.wisc.edu},
}

@MISC{ncr,
    title = {{National Cyber Range, DARPA-BAA-08-43}},
    howpublished = {http://www.darkgovernment.com/news/darpa-national-cyber-range/},
}
